Deploy an AI Analyst to Bruin Cloud & Slack
Build a stock market AI analyst in Bruin Cloud and connect it to a Slack AI agent so your team can query data from any channel.
Overview
Goal — Build a stock market AI analyst in Bruin Cloud and connect it to a Slack AI agent.
Audience — Data professionals who want to deploy an AI analyst to Bruin Cloud and make it available in Slack.
Prerequisites
- Bruin CLI installed and authenticated
- Claude Code available for pipeline generation and
bruin ai enhance - A Bruin Cloud account with access to Team settings and Projects
- A Git repo containing your Bruin project
- Slack workspace with bot credentials and channel access
Steps
1) Initialise the Bruin project
- Run
bruin init empty <pipeline-name>. If the current folder is already git-initialised, this creates<pipeline-name>unless you pass--in-place. - If the current folder is not a git repo, Bruin creates a
bruin/folder first and then creates the project and pipeline inside it. - For more context, see Bruin project docs and video walkthrough.
2) Build the pipeline
- Use Claude to extract stock data from Yahoo Finance and Wikipedia.
- Build assets that clean and join the data.
3) Enhance metadata
- Run
bruin ai enhanceacross the assets. - See AI enhance command for flag options.
- Confirm descriptions, column metadata, quality checks, and lineage look correct.
4) Add the repo to Bruin Cloud
- Go to Bruin Cloud, open Team settings, then Projects.
- Add the repo to the workspace.
- Enable the pipeline and run it.
- Confirm backfill runs and daily schedule work as expected.
5) Create the AI agent in Bruin Cloud
- Go to Agents and create a new agent.
- Select the repo and pipeline.
- Add Slack credentials.
- Name the agent and select the target Slack channel.
6) Add agent instructions
- Create an
AGENTS.mdfile in the project root with pretext, context, rules, and instructions. - Require
bruin queryfor all data access, and use--dry-runwhile testing.
7) Test in Bruin Cloud UI
- Ask a few questions to verify the agent can query the data.
- Confirm it can self-correct when the first query is not correct.
8) Test in Slack
- Mention the agent in a Slack channel.
- Ask a stock market question.
- Open the generated SQL to validate the logic.
- Request a PDF report and confirm it is generated.
Sample prompts
- "Which companies had their free cash flow margin improve in the past 4 quarters but saw their stock price decrease more than 10% during the same period?"
- "Summarize the top 10 tickers by revenue growth and generate a PDF report."
Helpful links
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